Category Archives: Artificial Intelligence

The growing demand for AI-based solutions and the need to analyze a complex and large amount of data is driving the market for Enterprise Artificial Intelligence.

Market Size USD 2,879.5 Million in 2020, Market Growth CAGR of 45.3%, Market Trends a Digitalization of enterprises.

The globalenterprise artificial intelligence (AI) marketis forecast to reach USD 59.17 Billion by 2028, according to a new report by Reports and Data. With the advancements in technology, enterprises are taking advantage of intelligent automation, such as machine learning, to improve the operations of business, improve customer experience, and drive innovation.

Artificial Intelligence (AI) is transforming businesses across industries, delivering new opportunities through automated products. Machine learning falls under AI and is used to teach computers how to carry out various range of tasks by analyzing vast amounts of data. Interests in machine learning have increased owing to the breakthroughs in areas such as speech recognition, computer vision, and natural language understanding. Machine learning helps enterprises by automating large areas of work like back-office administration roles, customer contact center queries, and even eventually driving vehicles.

AI is expected to help advance the growth of IoT. With more and more data being produced from technologies like the IoT and virtual reality devices, AI and automation will be crucial in not only managing data but also in supporting the growing pressure on business networks. With businesses becoming more borderless, and far more competitive, AI and machine learning-powered networks are essential in enterprises to reduce complexity and repetition. However, concerns related to data security and privacy are hampering the market growth.

There are various different examples of major enterprises using machine learning: Rolls Royce uses it to analyze data from IoT sensors to spot telltale signs of wear in its engine of the plane and carry out required maintenance. Google uses DeepMinds reducing energy to cool its data centers by about 40%.

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Further key findings from the report suggest

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For the purpose of this report, Reports and Data have segmented into the global Enterprise Artificial Intelligence (AI) market on the basis of component, application area, organization size, deployment mode, end-users, and region:

Component Outlook (Revenue: USD Billion; 2018-2028)

Application Area Outlook (Revenue: USD Billion; 2018-2028)

Organization Size Outlook (Revenue: USD Billion; 2018-2028)

Deployment Mode Outlook (Revenue: USD Billion; 2018-2028)

End Users Outlook (Revenue: USD Billion; 2018-2028)

Regional Outlook (Revenue: USD Billion; 2018-2028)

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Enterprise Artificial Intelligence (AI) Market Size Expected To Reach USD 59.17 Billion CAGR of 45.3%, By 2028 - Digital Journal

Cleveland Clinic and PathAI, a Boston-based artificial intelligence company, are teaming up to build what they call a "digital pathology infrastructure" and advance the use of AI-powered pathology algorithms in research and clinical care.

The health system and the company on Thursday, March 10, announced a five-year strategic collaboration that they said "will focus on leveraging PathAI's quantitative pathology algorithms both to conduct new translational research and for use as clinical diagnostics in multiple disease areas." They said the effort "combines PathAI's AI-based platforms with Cleveland Clinic's clinical expertise and multi-modal data to unlock a broad implementation of next-generation pathology diagnostics."

Dr. Brian Rubin, chair of the Pathology & Laboratory Medicine Institute at the Clinic, said in a statement, "Our commitment is to provide the best possible care for our patients, and it is increasingly clear that AI-powered pathology can radically enhance diagnostic accuracy and treatment selection."

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The Clinic and PathAI said the collaboration "will enable the digitization of hundreds of thousands of pathology specimens, creating millions of whole slide images across multiple disease areas." It also will "provide educational opportunities for Cleveland Clinic faculty and trainees, with the goal of enabling the development and usage of AI-powered pathology diagnostics to improve patient care," according to the release.

The Clinic said it will become an equity holder in PathAI as part of the agreement. Terms of that stake were not disclosed.

Dr. Andy Beck, CEO of PathAI, said in a statement, "We see an incredible opportunity to accelerate innovation in precision pathology and to use our strengths to bridge communities in the healthcare ecosystem including patients, biopharma and academic research."

This story first appeared in our sister publication, Crain's Cleveland Business.

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Cleveland Clinic enters five-year collaboration agreement with Boston artificial intelligence company - Modern Healthcare

AI is set to continue disrupting business operations, and increasingly drive value.

This article will explore how artificial intelligence is set to impact organisations in the future, gauging the insights of experts in the space.

Artificial intelligence (AI) is changing how businesses work and interact with their processes, products and people on both the employee and client side of operations. Gartner predicts the worldwide AI software market to reach $62 billion in 2022, an increase of over 20%. This digitisation is game-changing for companies in all sectors, as it underpins smarter, more streamlined and more cost-effective running of businesses, as well as driving more agile operations in todays disruptive climate.

With this in mind, we take a look at the possible future impact of artificial intelligence, as the technology continues to develop and infiltrate more business use cases.

Five AI predictions for 2022: from enterprise to everyday AI

Florian Douetteau, CEO of Dataiku, provides his five enterprise and everyday AI predictions for 2022. Read here

Organisations of all sizes, across multiple sectors, look set to continue deploying AI as part of their business strategy. By taking a step back and applying a joined-up, strategic approach to implementing AI-enhanced technologies such as intelligent automation, leaders can derive clear business benefits, including but not limited to improved customer service, increased competitiveness, greater productivity, and a more satisfied workforce.

Eric Tyree, head of research and AI at Blue Prism, explained: Whether its cutting customer wait times in financial services, enabling a more resilient and agile supply chain, or improving patient care by minimising manual admin work, intelligent automation can be the key driver in achieving strategic corporate initiatives.

Being ahead of the curve in this respect will have a significant impact on an organisations competitiveness within the market.

With AI-powered technologies in place to improve processes and transformation, organisations can then re-imagine how they operate, using a digital-first mindset. This, in turn, will allow staff to focus on more purposeful duties, including those focusing on customer service, and less on administrative functions.

Tyree continued: Relatively speaking, intelligent automation technology is the easy part of process improvement and transformation. Intelligent automation makes the implementation of operational reimagination much simpler and is having a huge impact on the way businesses are looking at their workforce, ways of working and capability to enact change that has strategic value to the business.

The capabilities digital robots possess lets the technology do the heavy lifting, allowing employees the capacity to take on more meaningful and complex work. The emphasis becomes a shift of human capital towards revenue generating or customer-centric activity, which gives way to enhanced capacity, more fulfilling work for staff, and more agility and scalability of resource across the entire organisation.

As more businesses make the commitment to AI and other transformative technologies, we will see this impact more and more organisations for the better across the globe.

In todays fast-paced digital and commercial world, organisations rely on networks to operate day-to-day. However, to deploy the networking services needed to meet the demands of this new hybrid working world will now need a network that utilises artificial intelligence and other autonomous capabilities.

Automation itself, and the idea that technologies can be self-provisioning, self-diagnosing, and self-healing, has existed for some time, explained John Morrison, senior vice-president of international markets at Extreme Networks.

But, thanks to advances in Artificial Intelligence (AI), autonomous networks are now becoming a reality. An autonomous network runs with minimal to no human intervention by configuring, monitoring, and maintaining itself independently. AI is now having a significant impact on businesses by replacing restrictive, error-prone networks and relieving overburdened IT teams tasked with finding and fixing problems instead of empowering and enabling people and connections.

Everyone can benefit from autonomous networks, driven by AI. For healthcare institutions, such networks have the ability to, for example, connect a medivac chopper to the doctors on the helipad or monitor the IV pumps that keep a patient alive. And for schools, a connected classroom can be created to help children overcome learning challenges through supportive software or monitor attendance to proactively keep at-risk students engaged in education.

Understanding your automation journey

Ravi Dirckze, technical product manager at HelpSystems, explains the need for businesses to understand their automation journey. Read here

On the customer side of things, users of digital services have been benefitting from AI deployments, which are proving to make engagement more efficient. While still relatively early in its development, artificial intelligence looks set to support bolstered personalisation and customisation over time.

As we enter the new metaverse era, we will only have access to increasing data points, meaning well be able to use AI more efficiently to create tailored experiences for customers, said Maja Schaefer, CEO and founder of Zowie.

In the future, our experiences with a brand will always be customised. For instance, when you enter a supermarket in the metaverse, the shelves will be stacked differently for others.

AI is already driving better online recommendations and targeted ads. In the future, it will go beyond and impact interactions as well. Over the last few years we have seen more and more practical applications of AI technology, and in the coming years, it will become widespread. As AI becomes part of our everyday life, its important to remember and care for privacy. Data being processed should always be anonymised and used only for specific purposes.

As AI continues to develop over the coming years, it will disrupt more operations across more sectors, leading to increased efficiency and decreased strain on workers going forward. The biggest impact from AI is set to come from those companies that can move their models into production most efficiently, and find ways to integrate those models best with their existing business processes.

Alex Housley, CEO and founder of Seldon, commented: The highest transformational potential for AI likely lies in healthcare; despite currently sitting at a 36% adoption rate, healthcare applications such as improved diagnostics or protein folding can deliver exceptional social and economic returns.

Were also beginning to see other industries like construction and logistics leverage ML models to optimise their services. For example, the construction industry is using ML to increase the accuracy of estimates when planning projects and improve safety by detecting potential risks on-site to prevent accidents.

Were also seeing AI perform better, owing to improvements in how developers create models, alongside the ability for us to compress models and run them on edge hardware allowing a greater variety of applications. AI is also becoming more accessible due to technologies like AI marketplaces, AI maker/teacher kits, and low-code/no-code AI platforms.

All in all, these improvements dramatically improved AIs use in industry, with nearly one in three enterprises having a model production by the end of 2021.

Manufacturing will see great potential for innovation, through an emerging framework called machine health. This capability uses the Internet of Things (IoT) and AI to predict and prevent industrial machine failures, and improve machine performance, via analytics.

Saar Yoskovitz, CEO and co-founder of Augury, expanded on how this is set to impact manufacturing operations in the future: AI is spearheading the fourth industrial revolution alongside technologies like automation and IoT capabilities.

Manufacturing is one of the industries already seeing a great benefit as AI is used to provide greater visibility into the processes, efficiency and capacity of these businesses. A key example is machine health a solution driven by AI to provide predictive analytics on critical and supporting equipment within manufacturing plants.

Sensors capture vibration, temperature and magnetic data from industrial machines, AI diagnoses machine issues based on that data and input from human reliability experts, explains what caused them and prescribes courses of action.

The impact of this AI use case is huge. When a critical machine fails, an entire production line grinds to a halt and that has serious upstream and downstream effects on entire supply chains. Machine health, therefore, allows manufacturers to strengthen their resilience against supply chain issues, or global events that impact production.

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The future impact of artificial intelligence - Information Age

RICHMOND, Va., March 10, 2022 /PRNewswire/ --SingleComm, the most powerful, affordable CCaaS solution available, is designing customized solutions that leverage industry-leading artificial intelligence (AI) tools while maintaining an authentic human touch.

"We've always provided our clients with advanced technologies, whether that's IVR or drag-and-drop workflows, and we're currently designing AI solutions that can be real-game changers for building efficiencies into staffing," says Michael Puccinelli, CEO and founder of SingleComm. "Like any other tool, AI should be viewed as something that can improve the performance of the humans on your team rather than something that replaces them altogether. Our solutions do just that."

SingleComm's approach to AI is aimed at increasing productivity by enhancing the skills of contact center representatives. Machine learning continues to make strides that were unimaginable just a few years ago, but AI programs only perform the functions they are designed to perform. In other words, tech shouldn't be perceived as something that can take over a contact center; it should be leveraged to make contact centers more efficient. It should also be customized to best meet a client's specific needs.

SingleComm's AI solutions streamline processes and tasks to improve efficiencies and free up teams to focus on exceptional customer service. Benefits include:

Personalization SingleComm's AI can tailor the customer experience based on information the platform has learned about the caller and his/her needs and attributes.

AI-Based Customer Routing The ability to match customers with the best resource or agent increases contact center efficiency while saving the customer's time.

Chatbots and Conversational Assistants These tools interact with customers by text or voice, taking care of simple and/or repetitive issues. When utilized correctly, these tools free up contact center representatives to focus on more complex assistance needs.

Workforce Management SingleComm's software has data analysis capabilities that help predict when agents and resources are needed.

Post Call Wrap-Up AI helps representatives enter call-action summaries and wrap-up codes. This limits the valuable time that representatives use to spend on "busy work."

Pucinelli adds, "Now more than ever, it is critical that contact centers be prepared to deliver immediate assistance around the clock. Our tight labor market has increased the degree of difficulty surrounding this deliverable. AI can significantly improve call center readiness, and we believe these technologies should work in concert with representatives, amplifying their skills while providing customers the human touch they expect and want."

For more information on SingleComm's use of AI or to speak with a solutions provider, please visit SingleComm.com.

Press Contact: Shea Communications, Richard Shea (917) 584-3542, [emailprotected]

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SingleComm Leverages Artificial Intelligence to Amplify Human Performance and Increase Customer Satisfaction - PR Newswire

In three previous blog posts, we have discussed recent inventorship issues surrounding Artificial Intelligence (AI) and its implications for life sciences innovations focusing specifically on scientist Stephen Thalers attempt to obtain a patent for an invention created by his AI system called DABUS (Device for Autonomus Bootstrapping of Unified Sentence). Most recently, we considered Thalers appeal of the September 3, 2021 decision out of the Eastern District of Virginia, which ruled that under the Patent Act, an AI machine cannot qualify as an inventor. Continuing this series, we now consider the USPTOs recently filed opposition to Thalers appeal.

In its opposition brief, the USPTO argued that under the plain language Congress chose to incorporate in the Patent Act, only a human being can be considered an inventor. The USPTO first noted that the definitions of inventor and joint inventor under the Patent Act both unequivocally refer only to an individual or individuals. For example, inventor is defined under the Act as the individual or, if a joint invention, the individuals collectively who invented or discovered the subject matter of the invention.

While the Patent Act does not explicitly define the term individual, the USPTO argued that in other instances where the term is not explicitly defined, courts have interpreted Congresss use of the term individual in a given statute as denoting a human being, as opposed to other things. The USPTO provided the example of Mohamad v. Palestinian Auth., a 2012 case in which the Supreme Court evaluated whether Congresss use of the term individual in the Torture Victim Protection Act (TVPA) could be construed to include an organization. There, the Court quoted from several well-known dictionaries and considered the use of the term in everyday parlance, to determine that the ordinary meaning of the term individual refers only to a human being or natural person. The Court in Mohamad also referred to the Dictionary Act, 1 U.S.C. 1, which provides that the legislative use of the term individual denotes something separate and apart from non-human beings.

The USPTO argued that the Supreme Courts analysis in Mohamad is equally applicable to the Patent Act as it is to the TVPA. For example, the term individual is used in the Patent Act as a noun, just as it is in the TVPA. And, according to the USPTO, just as the Mohamad Court recognized no onerefers in normal parlance to an organization as an individual, it is equally true that no one refers in normal parlance to a machine or collection of source code as an individual. Further, the USPTO pointed out that the Dictionary Act applies not only to the TVPA, but to all congressional enactments including the Patent Act.

Though the Supreme Courts opinion in Mohamad acknowledges that Congress is free to give the term individual a broader or different meaning, such broader construction by a court requires some affirmative indication [that Congress] intended such a result. Here, the USPTO argues that Thaler has never pointed to any textual evidence that Congress intended a broader meaning for the term. The USPTO argues that Thaler has only put forth non-textual policy arguments. For example, Thaler argues that denying inventorship to AI would place the United States behind other countries [that] are promoting the progress of science, and would amount to adopt[ing] luddism. However, according to the USPTO, these policy considerations cannot overcome the plain meaning of the text.

We will continue to monitor this appeal, as it has important implications for life sciences companies employing AI technologies, particularly given the low probability that Congress will act on this issue in the short term.

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Update on Artificial Intelligence: USPTO Urges Federal Circuit to Affirm Decision That AI Cannot Qualify as an Inventor - JD Supra

6 Ways Data Science and Artificial Intelligence is Driving Innovation to Help the Environment

Data science is preparing data for analysis. Artificial Intelligence (AI) is the implementation of a predictive model to forecast future events and helps computers or machines or robots controlled by computers to work as an alternative to humans.

With Data Science and AI becoming a transformative phenomenon for businesses and consumers, its vital to how it impacts the environment and embraces the challenges confronted in an increasingly populated, polluted and competitive world. The global AI and data science market is estimated to value more than $309 billion and $230 billion respectively. The technological advancements and initiatives in this field could have a significant impact on the environment.

Electric vehicles are good for the environment. They generate lesser greenhouse gases and cause less pollution. It is true even if we account for the electricity required to use them. Unmanned or automated driving, studying driver behaviour patterns, GPS navigation systems are some advancements where AI is playing a key role in the EV Industry. The implementation of AI in improving EVs, facilitating EV charging stations, and EV integration with the smart grid will encourage people to adopt electric vehicles and open a new pathway of eco-driving thus helping reduce greenhouse gas emissions.

As per research, in India more than 50 kg of food is wasted per person in a year, calculating to about 68,760,163 tonnes and is ranked at 94th position out of 107 countries. In fact, every country generates food waste at the consumer level irrespective of their income levels.

Given the pressure on already severely depleted soils to provide food for an ever-growing global population and the fact that roughly a third of food is never eaten, innovative AI technology can be used for overcoming this issue. Retailers can use AI to check and dispose of food items before they turn bad. Data analysis helps to calculate and predict the volume of food consumption in restaurants and households for them to reduce food waste eventually. Besides, AI could significantly improve packaging, increase the shelf life of food items, avoid food wastage by making a more transparent supply chain management system.

The recycling system of waste needs to be transformed urgently, as most of the waste generated over the year is mostly of single-use products. As per research in 2019, 660,787.85 tonnes of plastic waste was generated in India, out of which only 60% was recycled. One particular difficulty with recycling is the issue of segregation of waste. The use of robots that have sensors to separate different types of waste will help in a quicker and easier way of recycling as each product varies in its texture, shape and size. AI can also be used for creating an automated waste disposal system. Another way is by using image recognition technology which helps to collect information on waste and find alternative material solutions, eventually improving the recycling pattern of waste.

Sewage pollution is yet another concern, especially here in India. The major cause of increasing sewage pollution is that most of the problems go undetected. However, the use of pattern recognition, an AI technique, would help to monitor and track the wastewater flow. Besides, algorithms can detect patterns and create critical data for research and analysis for future improvements.

Over the years, the population of wildlife species has been continuously depleting. AI and data science help environmentalists to study the movement of animals and other species, their behaviour, the routes they follow their reproduction and hunting patterns. It helps curtail poaching and is an effective way of surveillance, for instance by using drones with cameras. Currently, there are environmental, sustainability projects taking place using AI and data science, to prevent forest fires and monitor wildlife. It also helps the environmentalists to monitor rare wildlife species populations and track them on cameras with smart sensors.

AI and data science can in the coming future be applied to thousands of issues affecting the environment. Data from various Space Research Centres can be used with help of AI technology to identify and monitor changes in land and sea areas, ice caps etc. Besides, data analysis can be done to reduce pollution and help fight Climate Change.

These technological solutions using AI and data science could help solve some of the most difficult environmental challenges.

Dr.MukeshKwatra,Founder of Smiling Tree

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Analytics Insight is an influential platform dedicated to insights, trends, and opinions from the world of data-driven technologies. It monitors developments, recognition, and achievements made by Artificial Intelligence, Big Data and Analytics companies across the globe.

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6 Ways Data Science and Artificial Intelligence is Driving Innovation to Help the Environment - Analytics Insight

Artificial intelligence is now used in virtually all aspects of our lives. Yet unchecked biases within existing algorithmic systems, especially those used in sensitive use cases like financial services, hiring, policing, and housing, have worsened existing societal biases, resulting in the continued systemic discrimination of historically marginalized groups. As banks increase AI usage in loan and appraisal decisions, these populations are subjected to an even greater precision in denials, eroding protections provided by civil rights laws in housing. Meanwhile, the use of facial recognition technologies among law enforcement has resulted in the wrongful arrests of innocent men and women of color through poor data quality and misidentification. These online biases are intrinsically connected to the historical legacies that predate existing and emerging technologies and stand to challenge the policies created to protect historically disadvantaged populations. Can civil rights and algorithmic systems coexist? And, if so, what roles do government agencies and industries play in ensuring fairness, diversity, and inclusion?

On TechTank, Nicol Turner Lee is joined by Renee Cummings, data activist in residence and criminologist at the University of Virginias School of Data Science, and Lisa Rice, president and CEO of the National Fair Housing Alliance. Together, they conduct a deep dive into these difficult questions and offer insight on remedies to this pressing question of equitable AI.

You can listen to the episode and subscribe to theTechTank podcastonApple,Spotify, orAcast.

TechTank is a biweekly podcast from The Brookings Institution exploring the most consequential technology issues of our time. From artificial intelligence and racial bias in algorithms, to Big Tech, the future of work, and the digital divide, TechTank takes abstract ideas and makes them accessible. Moderators Dr. Nicol Turner Lee and Darrell West speak with leading technology experts and policymakers to share new data, ideas, and policy solutions to address the challenges of our new digital world.

All Eye Overlordby Aswin Behera is licensed underCC BY 4.0

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TechTank Podcast Episode 39: Civil rights and artificial intelligence: Can the two concepts coexist? - Brookings Institution

Research and innovation in artificial intelligence (AI) in the power industry operations and technologies sector has declined in the last year. The most recent figures show that the number of AI-related patent applications in the industry stood at 84 in the three months ending January down from 191 over the same period in 2020.

Figures for patent grants related to AI followed a similar pattern to filings shrinking from 64 in the three months ending January 2020 to 10 in the same period in 2021.

The figures are compiled by GlobalData, which tracks patent filings and grants from official offices around the world. Using textual analysis, as well as official patent classifications, these patents are grouped into key thematic areas, and linked to key companies across various industries.

AI is one of the key areas tracked by GlobalData. It has been identified as being a key disruptive force facing companies in the coming years, and is one of the areas that companies investing resources in now are expected to reap rewards from.The figures also provide an insight into the largest innovators in the sector.

Siemens was the top AI innovator in the power industry operations and technologies sector in the latest quarter. The company, which has its headquarters in Germany, filed 51 AI-related patents in the three months ending January. That was down from 125 over the same period in 2020.

It was followed by the US-based Honeywell International with 21 AI patent applications, South Korea-based Korea Electric Power (19 applications), and the US-based 3M (10 applications).

Korea Electric Power has recently ramped up R&D in AI. It saw growth of 68.4% in related patent applications in the three months ending January compared to the same period in 2020 the highest percentage growth out of all companies tracked, with more than 10 quarterly patents in the power industry operations and technologies sector.

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Artificial intelligence innovation among power industry companies has dropped off in the last year - Power Technology

An analytic predictive study for the future of artificial intelligence and metaverse in 2030

With the pace artificial intelligence is intertwining within our lives, there is no doubt that it will not end anytime soon. Rather, the future looks like a society that would breathe and thrive through artificial intelligence only. Experts believe that specialized AI applications will become both increasingly common and more useful by 2030, improving our economy and quality of life. On the other hand, metaverse already has us wrapped in its not so little fingers. From Facebook to Instagram, virtual reality, Whatsapp, and many more, it is quite predictable that by 2030, its empire would only grow further.

A report published from Harvard University presents the eight areas of human activity in which Artificial intelligence technologies are already affecting urban life and will be even more pervasive by 2030: transportation, home/service robots, health care, education, entertainment, low-resource communities, public safety and security, employment, and the workplace will be fully AI-enabled spaces. Some of the biggest challenges in the next 15 years will be creating safe and reliable hardware for autonomous cars and healthcare robots; gaining public trust for Artificial intelligence systems, especially in low-resource communities; and overcoming fears that the technology will marginalize humans in the workplace.

Weve seen a lot of breakthroughs in data analytics. The example of Watson which is an IBM set of algorithms has been very impressive in terms of managing large amounts of data, and ways of structuring the data so that you can see patterns that may have not emerged otherwise. That has been an important leap. But oftentimes, people confuse that leap with machine intelligence and the way that we think about intelligence for humans and its simply not true. So the big leaps that we have had recently in data analytics are important but it also leaves a lot of room for humans to assist these systems. So, it can be said that the wave of the future is the collaboration of humans and these artificial intelligence technologies.

In its fully realized form, the metaverse promises to offer true-to-life sights, sounds, and even smells, whether a tour of ancient Greece or a visit to a Seoul caf can happen from your home. Decked out with full-spectrum VR headsets, smart clothing, and tactile-responsive haptic gloves, the at-home traveler can touch the Parthenon in Athens or taste the rich foam of a Korean dalgona coffee. You wouldnt even have to be you. Members of the metaverse could prowl the Brazilian rainforest as a jaguar or take the court at Madison Square Garden as LeBron James. The only limits are your imagination. It is also expected that using a blend of physical and behavioral biometrics, emotion recognition, sentiment analysis, and personal data, the metaverse will be able to create a customized and enhanced reality for each person.

While the metaverse industry is growing fast, fueled by the pandemic keeping people at home, its an open question as to whether one company will eventually emerge as the dominant force, such as Google, which now has a near-monopoly among search engines. One positive side of this trend is that since it is a virtual platform, the chances of people actually getting physically hurt will lessen, and also it will encourage them to get out of their comfort zone to try new things. The only wondering question left to ask on this matter will be the legal implications of the metaverse. For example, whether a marriage in the metaverse will be legal or if someone is assaulted in the metaverse, how the convict will be penalized. With the virtual avatar trend, there are huge chances of false identity or theft of identity, so recognizing the right person and their physical address can be a difficult job. This should be a major concern for all of the countries and their legislative and crime division.

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Looking at 2030: The Future of Artificial Intelligence and Metaverse - Analytics Insight

MILAN, March 10, 2022 /PRNewswire/ --Dedalus Group("Dedalus"), the leading healthcare and diagnostic software solutions provider in Europe, and Ibex Medical Analytics("Ibex"), the market leader in artificial intelligence (AI)-powered cancer diagnostics, today announced a strategic partnership to bring the power of artificial intelligence to digital pathology.

The partnership will bring the power of Ibex's clinical-grade AI algorithms into Dedalus' end-to-end digital pathology solution. This will benefit pathologists and patients through enhanced quality of diagnosis, at speed.

The increasing demand for pathology services posed by the growing number of cancer patients and global shortage of trained pathologists, leads pathology laboratories to actively seek efficiency-enhancing solutions that enable them to maintain high accuracy levels and reduce time to diagnosis.

Dedalus' end-to-end digital pathology solution addresses the needs of anatomic pathology labs and ensures interoperability with existing multi-vendor solutions, enabling a seamless, gradual evolution towards full digitization to meet the increasing demands of the healthcare system.

With over 30 years' experience in laboratory solutions, Dedalus has deployments in over 5700 laboratories globally, and has been instrumental in successfully bringing cutting-edge technologies into the laboratories to make the systems as agile, efficient, and accurate as possible.

Ibex transforms cancer diagnosis by harnessing AI and machine learning technologies at an unprecedented scale. The company's Galen platform has demonstrated outstanding outcomes in multiple clinical studies on various tissue types and clinical workflows. It is deployed in labs worldwide where it is used as part of everyday clinical practice.

Ibex's clinical-grade AI algorithms will seamlessly integrate into Dedalus end-to end digital pathology solution, enabling smooth workflows from a single application. The joint solution will analyse cases prior to human pathologists' review, providing decision support tools that will enable increased focus on cancerous slides and areas of interest, streamline reporting, improve laboratory efficiency, and increase diagnostic confidence.

"Dedalus is the leading healthcare and diagnostic software provider in Europe. As part of our commitment to accelerate the digital transformation in healthcare, we strongly believe in the value of artificial intelligence, specifically in pathology and cancer diagnoses. Therefore, we are proud to partner with Ibex Medical Analytics, which is a global leader in AI-powered solutions for pathology labs and cancer diagnostics," said Marlen Suller, Head of In Vitro Diagnostics Business Unit at Dedalus.

"Our AI solutions transform pathology and help physicians around the world provide on-time, quality diagnosis to patients," said Joseph Mossel, CEO and Co-founder of Ibex Medical Analytics. "Yet to unlock the full potential of artificial intelligence, pathologists and health systems need AI-enabled workflows and integrated cancer pathways. We are excited to partner with market leaders Dedalus and to deliver end-to-end diagnostic modalities that improve the way laboratories work and support better cancer care."

ABOUT DEDALUS

Dedalus Group is the leading healthcare and diagnostic software provider in Europe, supporting the digital transformation of 6300 hospitals and 5700 Laboratories worldwide, processing its solutions for more than 540 millions of population worldwide. Dedalus supports the whole continuum of care, offering open standards-based solutions serving each actor of the Healthcare Ecosystem to provide better care in a healthier planet.

For more information, visitwww.dedalus.com

ABOUT IBEX MEDICAL ANALYTICS

Ibex pioneers AI-powered cancer diagnostics in pathology. We empower physicians to provide every patient with an accurate, timely and personalized cancer diagnosis by developing clinical-grade AI algorithms and digital workflows that help detect and grade cancer in biopsies. Our Galen platform is the first-ever AI-powered integrated diagnostics solution in pathology and used in routine clinical practice worldwide, supporting pathologists and providers in improving the quality and accuracy of diagnosis, implementing comprehensive quality control, reducing turnaround times and boosting productivity with more efficient workflows.

For more information, visitwww.ibex-ai.com

CONTACT

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Dedalus and Ibex announce a strategic partnership to bring the power of artificial intelligence to digital pathology - PR Newswire